I've been diving into the inner workings of language models like ChatGPT and got curious about one of their intriguing features—the ability to rhyme. For instance, when given prompts to generate rhymes about various topics, you get coherent and rhythmically pleasing responses. But how's this magic happening under the hood? I know transformer models generate text one token at a time and use past tokens to predict the next ones, but it seems like they must be planning out rhymes somehow. Do newer versions of models have internal mechanisms for this? Anyone have insights or explanations?
1 Answer
It's actually been researched by Anthropic! They found that language models do use some planning when generating rhymes. The research indicates that LLMs like ChatGPT can activate potential rhyming words before composing a line, which helps them create sentences that naturally lead to the rhyme. This means they aren't just throwing words together at random, but rather, they have an internal strategy for making rhymes feel smoother and more natural. You can check their paper for more detailed insights!
Thanks for the heads up! I gotta look into that paper. It sounds like it has a lot of fascinating information about how LLMs think.